Diagnostic applications of Raman spectroscopy

Raman spectroscopy detection of molecular changes associated with two experimental models of osteoarthritis in rats

The aim of the present study was to evaluate the feasibility of applying Raman spectroscopy in probing the molecular changes in terms of collagen deposition and tissue remodeling associated with two well-established experimental models of osteoarthritis (OA) in knee of rats. In order to evaluate alterations in the articular surface area, the menisci-covered tibial region was assessed into three groups as follows: control (joint preserved) and two models of experimental knee OA: collagenase-induced model (n = 8) and treadmill exercise-induced model (n = 8). Each group was examined for molecular changes using spectral parameters related to cartilage, subchondral bone, and bone tissues. A significant increase of Raman ratios related to mineralization and tissue remodeling was found (p < 0.05), suggesting that both models were successful for inducing OA in rats. The significantly lower phenylalanine content and higher crystallinity in the treadmill exercise-induced model of OA than collagenase-induced model of OA (p < 0.05) indicated that the OA pathogenesis was model-dependent. Thus, this work suggests that the Raman spectroscopy technique has potential for the diagnosis and detection of cartilage damage and monitoring of subchondral bone and bone in OA pathogenesis at the molecular level.

Raman microspectroscopy as a biomarking tool for in vitro diagnosis of cancer: a feasibility study

Aim

To elucidate whether Raman spectroscopy aided by extensive spectral database and neural network analysis can be a fast and confident biomarking tool for the diagnosis of various types of cancer.

Methods

Study included 27 patients with 11 different malignant tumors. Using Raman microscopy (RM) a total of 540 Raman spectra were recorded from histology specimens of both tumors and surrounding healthy tissues. Spectra were analyzed using the principal component analysis (PCA) and results, along with histopathology data, were used to train the neural network (NN) learning algorithm. Independent sets of spectra were used to test the accuracy of PCA/NN tissue classification.

Results

The confident tumor identification for the purpose of medical diagnosis has to be performed by taking into account the whole spectral shape, and not only particular spectral bands. The use of PCA/NN analysis showed overall sensitivity of 96% with 4% false negative tumor classification. The specificity of distinguishing tumor types was 80%. These results are comparable to previously published data where tumors of only one tissue type were examined and can be regarded satisfactorily for a relatively small database of Raman spectra used here.

Conclusion

In vitro RM combined with PCA/NN is an almost fully automated method for histopathology at the level of macromolecules. Supported by an extensive tumor spectra database, it could become a customary histological analysis tool for fast and reliable diagnosis of different types of cancer in clinical settings.

Design and analysis of a squamous cell carcinoma in vitro model system

Tissue-engineered skin equivalents based on primary isolated fibroblasts and keratinocytes have been shown to be useful tools for functional in vitro tests, including toxicological screenings and drug development. In this study, a commercially available squamous cell carcinoma (SCC) cell line SCC-25 was introduced into epidermal and full-thickness skin equivalents to generate human-based disease-in-a-dish model systems. Interestingly, when cultured either in the epidermis or dermis of full-thickness skin equivalents, SCC-25 cells formed hyper-keratinized tumor cell nests, a phenomenon that is frequently seen in the skin of patients afflicted with SCC. Raman spectroscopy was employed for the label-free cell phenotype characterization within the engineered skin equivalents and revealed the presence of differential protein patterns in keratinocytes and SCC-25 cells. To conclude, the here presented SSC disease-in-a-dish approaches offer the unique opportunity to model SSC in human skin in vitro, which will allow further insight into SSC disease progression, and the development of therapeutic strategies.

Optical techniques for the noninvasive diagnosis of skin cancer

PURPOSE

The aim of this paper is to provide an overview of the most investigated optical diagnostic techniques: optical coherence tomography, fluorescence spectrometry, reflectance spectrometry, Raman spectroscopy, and confocal microscopy.

METHODS

A search of three databases was conducted using specific keywords and explicit inclusion and exclusion criteria for the analysis of the performances of these techniques in the pre- and postoperative diagnosis of skin cancers.

RESULTS

Optical coherence tomography has shown promising results in the assessment of deep margins of skin tumors and inflammatory skin diseases, but differentiating premalignant from malignant lesions proved to be less effective. Fluorescence spectroscopy proved to be effective in revealing the biochemical composition of tissue; early detection of malignant melanoma was reliable only with stepwise two-photon excitation of melanin, while tumoral margin assessment and differential diagnosis between malignant and non-malignant lesions showed some conflicting results. Characterization of the structural properties of tissue can be made using diffuse reflectance spectrometry, and the values of the specificity and sensitivity of this method are ranging between 72-92 % and 64-92 %, respectively. Raman spectroscopy proved to have better results both in carcinoma and melanoma diagnosis with sensitivities and specificities above 90 % and high above 50 %, respectively. Confocal microscopy is the closest technique to pathological examination and has gained the most clinical acceptance, despite the need for a standardization of the interpretation algorithm.

CONCLUSIONS

In conclusion, these optical techniques proved to be effective in the diagnosis of skin cancer, but further studies are needed in finding the appropriate method or combination of methods that can have wide clinical applications.

Raman-on-chip device and detection fibres with fibre Bragg grating for analysis of solutions and particles

An all-fibre based Raman-on-chip setup is introduced which enables analysis of solutions and trapped particles without microscopes or objectives. Beside the novel quartz microfluidic chip, innovative multi-core single-mode fibres with integrated fibre Bragg gratings are used for detection. The limit of quantitation is 7.5 mM for urea and 2.5 mM for nicotine with linear Raman spectroscopy. This is an improvement of more than two orders of magnitude compared with previous fibre-based microfluidic Raman detection schemes. Furthermore, our device was combined with optical traps to collect Raman-on-chip spectra of spherical polymer beads.

Multicore fiber with integrated fiber Bragg gratings for background-free Raman sensing

In the last years a variety of fiber optic Raman probes emerged, which are only partly suited for in vivo applications. The in vivo capability is often limited by the bulkiness of the probes. The size is associated with the required filtering of the probes, which is necessary due to Raman scattering inside the fibers. We employed in-line fiber Bragg gratings (FBG) as notch filter for the collection path and integrated them in a novel type of Raman probe. Multicore singlemode fibers (MCSMF) were designed and drawn integrating 19 singlemode cores to achieve better collection efficiency. A Raman probe was assembled with one excitation fiber and six MCSMF with inscribed FBGs as collection fibers. The probe was characterized regarding Raman background suppression, collection efficiency, and distance dependence. First Raman measurements on brain tissue are presented.